class_docstr: Quantizer for handling weights in Conv2DTranspose layers.
code: def __call__(self, inputs, training, weights, **kwargs):
      outputs = tf.transpose(inputs, (0, 1, 3, 2))
      outputs = super(
          DefaultNBitConvTransposeWeightsQuantizer, self
      ).__call__(outputs, training, weights, **kwargs)
      outputs = tf.transpose(outputs, (0, 1, 3, 2))
      return outputs
  
file_path: model-optimization/tensorflow_model_optimization/python/core/quantization/keras/experimental/default_n_bit/default_n_bit_quantizers.py
imports: import tensorflow
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
label_desc: Use image node_id 2 for calling the DefaultNBitConvTransposeWeightsQuantizer obj's underlying member method code with example usage: obj.__call__(inputs, training, weights) and returns: outputs